Primeiro projeto apresentado na disciplina de Inteligência Computacional em Saúde utilizando a base de dados de indicadores de saúde para tarefa de classificação de indivíduos com diabetes.
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Updated
Jun 14, 2024 - Jupyter Notebook
Primeiro projeto apresentado na disciplina de Inteligência Computacional em Saúde utilizando a base de dados de indicadores de saúde para tarefa de classificação de indivíduos com diabetes.
Este repositório contém uma implementação do algoritmo SVM para classificação de dados nos datasets Iris e Wine, usando a linguagem R com RStudio. Você pode executar o código localmente ou com Docker.
Model buat TA Sentimen and Topik Berita Indonesia
The primary objective is to deploy a robust classifier model that accurately predicts user recommendations, empowering airlines to strategize effectively, understand user behavior, optimize services, and align business strategies with financial objectives.
Feature Selection using Metaheuristics Made Easy: Open Source MAFESE Library in Python
Diabetes Prediction Using SVM Algorithm
BoW model in image classification
Here we have fully implemented a number of algorithms related to machine learning
The notebook contains Python code for various machine learning tasks and models. Here is an overview of its content:
Credit Score Classification in R using various algorithms
Support Vector Machine (SVM) is a supervised machine learning algorithm commonly used for classification and regression tasks. It works by finding the hyperplane that best separates the data into different classes.
This project aims to predict heart failure outcomes by applying statistical learning algorithms. The goal is to improve the prediction accuracy through the SuperLearner algorithm.
Bu projede Breast Cancer data veri seti kullanılarak KNN (K Nearest Neighbor) SVM (Support Vector Machine) Naive Bayes algoritmalarıyla eğitim yapılmıştır. Eğitimde Gridsearch kullanılarak en optimum parametreler bulunmuştur.
In this work, an automatic and reproducible methodology is proposed using computer vision techniques for sorting oranges by size and defects. Master thesis written in Spanish.
This project aims to clarify the role of meta data in music genre classification and how helpful or hurtful it can be to music recommendation systems. Much experimentation was done with multiple different machine learning models and results were analysed and collated into a single academic paper
Using Machine Learning in predicting customer churn from bank credit card services
Data Mining | Machine Learning
Educational notebooks reviewing machine learning models and concepts.
Skin Cancer Detection: Leveraging Hybrid Deep Learning Models and Traditional Machine Learning Classifiers
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